The present application relates to image fusion (e.g., also referred to as image registration). It finds particular application in medical examinations and/or treatments where viewing an object using two or more image modalities may be useful. For example, as provided herein, images yielded from examining an object using a first image modality may be correlated with images yielded from examining the object using an ultrasound modality based upon a transformation matrix that is automatically generated. In this way, as medical personnel alter the view of an object as represented in ultrasound images, a view of the object as represented in images yielded from the first image modality may be automatically altered in a corresponding manner such that both images that are displayed on a screen represent a substantially similar viewpoint of the object, for example. It will be appreciated that while particular reference is made herein to medical applications, the features described herein may also be applied to other applications, such as security and/or industrials applications.
Today, a plurality of image modalities exists for imaging an object under examination. The particular image modality that is used may depend upon numerous factors, including, but not limited to, which aspect(s) of the object a medical professional desires to examine. For example, medical sonography (e.g., one form of ultrasound) is frequently used to visualize muscles, tendons, and/or organs of a patient, whereas conventional x-ray systems are typically used to visualize the skeletal system of a patient. Accordingly, it may be that, in some applications, such as in numerous medical applications, an aspect of an object to be examined and/or treated may be imaged using more than one image modality to leverage off of the respective benefits of different modalities. For example, computed tomography (CT) systems have become an important tool to supplement x-rays and medical sonography because CT systems can generally produce higher contrast images than x-ray systems and/or ultrasound systems (e.g., such that differences between tissues that differ in density by less than 1% can be distinguished). Magnetic resonance imaging (MRI) systems are another type of image modality that has been used to supplement x-rays and medical sonography because of the contrast MRI systems provide in images.
To improve upon the usefulness (e.g., diagnostic advantages and/or treatment planning capabilities) of the data collected from two or more image modalities, a process known as image fusion may be performed. Generally speaking, image fusion is the process of combining or correlating relevant data from two or more image modalities. Traditionally, the data from the two image modalities was literally combined during image fusion, such that a technician was typically viewing a monitor that essentially comprised an image acquired from a first image modality overlaid on top of an image acquired from a second image modality. However, the more modern approach is to correlate but not combine the data from the two or more image modalities. Thus, an image representing a first perspective of an object acquired using a first image modality may be situated side-by-side on a monitor(s) with an image representing a substantially similar perspective of the object acquired using a second image modality. When a technician alters the perspective of the object as represented by an image acquired using the second image modality (e.g., which may be imaging the object in real-time), the perspective of the object as represented by an image acquired using the first image modality (e.g., which may have imaged the object weeks earlier) may be reoriented to reflect the alteration made to the orientation of the object represented in the image(s) acquired using the second image modality. In this way, a user is typically viewing side-by-side images, acquired from different image modalities, that depict an object from a substantially similar viewpoint.
While image fusion has proven successful for combining data collected using two or more image modalities, the ability to fuse or correlate data acquired from an ultrasound system with data acquired from another image modality (e.g., acquired at a same or different time) has proven to be elusive. For example, when a technician wishes to fuse ultrasound data with data acquired from another image modality and/or with ultrasound data acquired at a different time (e.g., such as weeks earlier), the technician generally manually aligns the ultrasound images with the images yielded from another image modality to generate a transformation matrix that is based upon the manual alignment. Such a manual alignment is generally time intensive, introduces human error, and can be performed merely by those with expertise in interpreting both ultrasound images and the images yielded from the other image modality(ies) with which the technician desires to fuse or correlate the ultrasound image(s).